Update app.py
Browse files
app.py
CHANGED
@@ -1,4 +1,3 @@
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import pandas as pd
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import numpy as np
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import pickle
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@@ -12,10 +11,15 @@ from transformers import AutoTokenizer, AutoModel, pipeline, AutoModelForQuestio
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from sentence_transformers import models, SentenceTransformer
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import torch
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import spacy
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import streamlit as st
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from utils import *
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@st.cache(allow_output_mutation=True)
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def load_prep_data():
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with open('listfile_3.data', 'rb') as filehandle:
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@@ -65,10 +69,12 @@ def load_comprehension_model():
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def main():
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nltk.download('punkt')
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spacy_nlp = spacy.load('en_core_web_sm')
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device = torch.device('cuda:0' if torch.cuda.is_available()
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else 'cpu')
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embeddings = load_prep_data()
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@@ -79,7 +85,7 @@ def main():
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comprehension_model = load_comprehension_model()
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query = st.text_input("Enter Query",'example query ',key="query")
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query_embedding, results1 = fetch_stage1(query, model, list_of_articles)
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import pandas as pd
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import numpy as np
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import pickle
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from sentence_transformers import models, SentenceTransformer
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import torch
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import spacy
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import subprocess
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import streamlit as st
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from utils import *
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@st.cache(allow_output_mutation=True)
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def load_spacy_model():
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subprocess.call(['python', '-m','spacy', 'download', 'en_core_web_sm'])
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@st.cache(allow_output_mutation=True)
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def load_prep_data():
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with open('listfile_3.data', 'rb') as filehandle:
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def main():
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nltk.download('punkt')
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load_spacy_model()
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spacy_nlp = spacy.load('en_core_web_sm')
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device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
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embeddings = load_prep_data()
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comprehension_model = load_comprehension_model()
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query = st.text_input("Enter Query",'example query ', key="query")
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query_embedding, results1 = fetch_stage1(query, model, list_of_articles)
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